A DISTRIBUTED INFRASTRUCTURE-AS-A-SERVICE PROVIDING CLOUD-BASED HIGH-PERFORMANCE COMPUTING WHITEPAPER Writen by: Dan Desjardins www.sparc.network August 2017
TABLE OF CONTENTS 03 ABSTRACT 04 INTRODUCTION 05 MARKET CHALLENGES AND OPPORTUNITIES 06 DISTRIBUTED NETWORK ARCHITECTURE AS A SOLUTION 08 CROWDFUNDING 09 MEET THE TEAM 10 CONCLUSION 11 REFERENCES 11 INDEXES 2
ABSTRACT Historically, access to high-performance computing systems has been limited to large firms possessing the human, technical, and financial resources required to own and operate them. As big data morphs into bigger data, computational problems spiral upwards in complexity, and new high-tech computation-dependent fields emerge, developers are seeking new tools and methods to employ. In response to this growing demand, companies including Amazon EC2 and Google Compute Engine have recently been offering cloud-based computing services to small to medium-size developers requiring computational resources to attain a myriad of objectives. However, as developers and market demand migrate towards cloud-based high-performance computing, existing centralized architectures will quickly become outpaced. Distributed computing is the only solution to this problem of scalability: a global network of computers is far more powerful than any supercomputer. The unaddressed challenge with this global architecture lies in the mediation of transactions between the users who commit the projects and the compute nodes that perform the work. SPARC is a distributed infrastructure-as-a-service that will dynamically allocate computational resources to user projects, using Science Power and Research Coins (SPARC) to quantify and remunerate completed computational work. Specifically, users requiring compute power purchase SPARC tokens from an exchange and attach them to their projects. These tokens are distributed to the computational resource owners in proportion to work performed. SPARC tokens can then be exchanged directly for computing power from the network or traded for conventional currency on an exchange. 3
INTRODUCTION In our era of exponential data growth, industry and academia is realizing that it must achieve a fundamental transformation in how operations are run and innovation is achieved. This transformation will require a step change in thinking and an openness that may not have been present before. The key lies in cloud adoption. Due to a convergence of multiple technologies, including ubiquitous wireless communication, real-time analytics, machine learning, and embedded systems, the commoditization of compute power resources is inevitable. Already, cloud computing has become a highly demanded service or utility due to the advantages of high computing power, cheap cost of services, high performance, scalability, accessibility as well as availability. The International Data Corporation (IDC) forecasts that the High-Performance Computing (HPC) sector will experience a Compounded Annual Growth Rate (CAGR) of 8 percent bringing total market to USD $31.4B by 2019 [1]. Infrastructure-as-a-Service (IaaS) is projected to grow 36.8% in 2017 to reach USD $34.6B [2]. Examples of computation-intensive sectors: Big Data and Business Analytics (BDA) Forecasts worldwide revenues for BDA will reach $150.8 billion in 2017, an increase of 12.4% over 2016. Commercial purchases of BDA-related hardware, software, and services are expected to maintain a CAGR of 11.9% through 2020 when revenues will be more than $210 billion. Science, Technology, Engineering and Mathematics (STEM) researchers and industries For example, the market for neural network software is projected to grow from USD $7.17B in 2016 to $22.55B by 2021 [3]. Driven by uncategorized and newly digitized data, neural networks are computation-intensive sorting machines. Video and Image rendering Rendering and visualization software is expected to grow at a compounded annual growth rate (CAGR) of 30.03% from 2016 to 2020 [4]. 3D enabled display devices, virtual and augmented reality, and high-end video games are driving this growth. Advanced Risk Analytics Risk analytics has a predicted CAGR of 15.3% bringing the market from USD $17.60B in 2017 to $35.92B by 2022 [5]. Emerging technologies such as artificial intelligence enable institutions to improve underwriting decisions and increase revenues while reducing risk costs. 4
MARKET CHALLENGES AND OPPORTUNITIES Centralized IaaS firms, examples listed in Figure 1, are emerging in response to an upward spiraling global demand for computing power. Public Cloud Revenue % Market Share 2017 36% Amazon Web Services, 47% Other 36% 10% 47% Microsoft Azure 10% Google Cloud Platform 4% IBM Softlayer 3% 4% 3% Figure 1: Public cloud revenue market share 2017 SPARC has identified the following opportunities and challenges in the existing market: High growth-rate of HPC requirements. A large market is available for competitive cloud-based computing services. A vast supply of computing resources exists in the form of underutilized personal and commercial computer assets. These resources can be networked to form a distributed IaaS platform providing high-performance computing power to science and industry. This architecture incurs limited additional infrastructure, operation and maintenance costs. Existing centralized IaaS providers incur higher costs to acquire, operate, maintain, update and expand costly infrastructure and dedicated hardware. Higher costs ultimately result in higher pricing; the customer pays for it. 5
DISTRIBUTED NETWORK ARCHITECTURE AS A SOLUTION SPARC is the first North American distributed IaaS providing consumers with affordable, flexible, and easily accessible high-performance cloud-based computing. To achieve this, we are Leveraging existing demand and infrastructure. The Berkeley Open Infrastructure for Network Computing (BOINC) is a computing platform comprised of 1,128,897 compute nodes. At 17.1 petaflops, it is the third most powerful supercomputer on Earth and supports computing projects in astrophysics, mathematics, and biology, for example. The alpha version of our network connects to the BO- INC network and rewards participant nodes with Science Power and Research Coins (SPARC) for computational work performed. Researchers and developers requiring computing power purchase SPARC tokens from an exchange and attach them to their projects. These tokens are distributed to the participant nodes in proportion to work performed. SPARC tokens can then be exchanged directly for computing power from the network or traded for conventional currency on an exchange. Recapturing wasted computing power. We have identified inefficiencies in existing blockchain currencies. For example, in the competition-based process of hashing a digital transaction on the Bitcoin network, approximately 5,000 peta hashes per second are discarded. This amount of wasted compute power is equivalent to approximately 64,000x the combined power of the Top 500 Supercomputers. Instead of hashing to determine proof-of-work, SPARC is compensating participant nodes for actual work performed. We are effectively recapturing wasted computing resources and making them available to science and industry. 6
Varying hardware allocation instead of varying pricing. Whereas Amazon EC2, Google Cloud Compute and other services vary the price as a function of system loads, our network varies the hardware dedicated to your service via an auction process. We allow you to set your price point and let the network compete for available jobs. This ensures 100% network usage, and potentially high rates of power at low cost without added setup for your project. Expanding infrastructure by connecting new compute assets to our cloud. Compute resource consumers can also participate as suppliers earning SPARC tokens that can be used to fund their own usage, or be traded for conventional currency on an exchange. This is an example of demand creating supply. SPARC foresees that imminently arriving self-driving automated vehicles, each containing Massively Parallel Processing (MPP) units, when not in operation, will network together forming one of the most powerful distributed supercomputers on Earth. The Internet of Things allows for any device to participate in our distributed computing network, earning SPARC for device owners and providing compute power for users. Low costs relating to infrastructure, operations, and maintenance translate directly into more affordable services for our users. 7
CROWDSALE Our second round is designed to open our network up to the broader public. Once the Alpha release has started gaining traction we will be turning our attention towards the proprietary network. This network will allow us to open up to commercialization and streamline delivery of content. We will be raising funds for progressing development towards release. Q1 2018 is our projected release for the minimum viable product. This release is targeted at bringing new users and agile projects onto the system. Moving forward we will be expanding support to niche cases and developing extensions for proprietary programs such as MatLab and COMSOL. Our goal is to establish a long term budget to ensure continuation of the network. This will give miners and projects confidence moving onto our platform. The minimum cap is set to ensure we have critical mass to launch our network. If we should fail to meet the minimum cap, we will be continuing to build support on our Alpha, and developing our network while aiming for a successful funding round in the future. Please do not send your purchase from an exchange address. If you do, your tokens can be recovered, but this is a manual process and may take several days involving proving your ownership of that address. Round 2 Tentative Start Date End Date Minimum Cap Maximum Cap Exchange Rate Round 1 Participant Bonus Bounty Tokens Developer Equity Crowdsale Contract Address Token Contract Address October 1st 2017 30 Days after start 250,000,000 SPARC 2,500,000,000 SPARC 1 ETH : 10000 SPARC Additional 100% to max of Round 1 Participation 1% of Tokens Sold 5% of Tokens Sold To Be Released Etherscan 8
MEET THE TEAM DOUGLAS STEWART FOUNDER, CEO A serial entrepreneur this will be Doug s third online company. His first successfully acquired, the second, Quetzal a leader in cloud based point-of-sale, is still growing. Doug is a team builder and with 20 years of management he brings valuable experience and connections to the company. GREG AGNEW FOUNDER, CTO, LEAD DEVELOPER Greg was a also founding member of the Quetzal four. Always at the forefront of technology, he has mastered Ethereum and full stack development. Spending his spare time building chess engine style games in web applications he is an expert in pushing V8 to the limits. DANIEL DESJARDINS, PHD VP OF BUSINESS DEVELOPMENT A serial entrepreneur this will be Doug s third online company. His first successfully acquired, the second, Quetzal a leader in cloud based point-of-sale, is still growing. Doug is a team builder and with 20 years of management he brings valuable experience and connections to the company. EDDIE ROOSENMAALLEN SYSTEMS ARCHITECT Eddie is a full-stack engineer with over a decade of experience in rich web apps on both physical and cloud deployments. He is a veteran teammate of ours, having worked together at both DAS and Vivonet. ANNE VIVIAN-SCOTT, MBA, PENG COMMERCIAL ADVISOR President and CEO BKIN Technologies The majority of my career has been occupied by the challenging task of commercializing university-based research discoveries into meaningful products and services. The KDS initiative is a timely innovation that will have the full support of researchers requiring distributed supercomputing power. MACK VAN ROSSEM RESEARCH ADVISOR Former South Pole data center operator for the IceCube Neutrino Observatory Mack has worked slicing data and sending it over networks for use back home. He has a passion for reducing wasted computational power and improving our efficiency with this critical resource. 9
CONCLUSION SPARC offers a truly disruptive solution to growing global demand for cloud- based, high-performance computing. Compared to centralized IaaS platforms, our network delivers cost-effective, flexible, and powerful computing power. The SPARC network can endlessly expand its infrastructure by connecting underutilized computer assets to the network, and recaptures wasted computing power from proof-of-hash blockchains. Our distributed architecture is sustainable and eco- friendly, promoting full usage of existing hardware instead of commissioning and operating new infrastructure. SPARC envisions a world in which anyone with a laptop and an internet connection will have the power of a supercomputer at their fingertips. 10
APPENDIX References [1] Feldman,M.(2016,Nov30).IDC slatestforecastforthehpcmarket: 2016 is Looking Good [Article]. Retrieved from https://www.top500.org/news/idcslatest-forecast-for-the-hpc-market-2016-is-looking-good/ [2] Pettey C. and Goasduff L. (2017, Feb 22). Gartner Says Worldwide Public Cloud Services Market to Grow 18 Percent in 2017 [Press release]. Retrieved from http://www.gartner.com/newsroom/id/3616417 [3] CISIONPRNewswire.(2017,Jan23).NeuralNetworkSoftwareMarketbyType, Vertical, and Region - Global Forecast to 2021 [Article]. Retrieved from http:// www.prnewswire.com/news-releases/neural-network-software-market-bytype- vertical-and-region---global-forecast-to-2021-300395057.html [4] [5] Business Wire. (2016, Mar 31). Visualization and 3D Rendering Software Market 2016-2020 - High-End Video Games, Architectural and Product Visualization, TrainingSimulation,MarketingandAdvertisement-ResearchandMarkets[Article]. Retrieved from http://www.businesswire.com/news/ home/20160331005465/en/ Visualization-3D-Rendering-Software-Mar- ket-2016-2020-- Markets and markets. (2017). Risk Analytics Market worth 35.92 Billion USD by 2022 [Article]. Retrieved from http://www.marketsandmarkets.com/ PressReleases/risk-analytics.asp INDEX SPARC Science Power and Research Coin BDA Business Data Analytics CAGR HPC IDC Compounded Annual Growth Rate High Performance Computing International Data Corporation BOINC Berkeley Open Infrastructure for Network Computing STEM Science, Technology, Engineering and Mathematics FLOPS Floating point operations per second IaaS Infrastructure-as-a-service MPP Massively Parallel Processing 11
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